Cloud computing is a model of service delivery for enabling convenient, on-demand network access to a shared pool of configurable computing resources (e.g. networks, network bandwidth, servers, processing, memory, storage, applications, virtual machines, and services) that can be rapidly provisioned and released with minimal management effort or interaction with a provider of the service. Structured cloud data includes spreadsheets and other similar databases and structures that are stored in the cloud.
Structured data may be subject to input errors and other variations or anomalies that negatively impact data quality. In the prior art the discovery of such errors and variations is often made long after negative effects on the structured data have occurred, for example, months after a found error has occurred and already generated bad data outputs over the intervening time from occurrence to detection.
Complex formulas, macros, and other programming solutions may be created and deployed within structured cloud data systems in order to avoid the effects of data errors and variations. However, such solutions require the expenditure of significant or sophisticated programming resources, and even then adequate programming solutions may be beyond the skills of many users. Other solutions for resolving these type of structured cloud data errors rely on manual review of the structured cloud data results by very experienced employees, which can be cumbersome costly in terms of available time and resources.